Exploring Materials Synthesis with MP Data and Reaction Networks¶

Author: Matthew McDermott
Last updated: 08/05/21

Goal¶

Learn how to build & interpret phase diagrams using MP data and apply these to predict reaction pathways in inorganic materials synthesis.

Outline¶

1. Identifying a target system
2. Building phase diagrams
3. Predicting interface reactions between solids
4. Enumerating all possible reactions to a specific target phase
5. Constructing a reaction network from enumerated reactions
6. Finding and balancing reaction pathways

1. Identifying a target system¶

Scenario:

While researching ferroelectric materials, you stumble upon a compound that has shown much promise as a multiferroic material: yttrium manganese oxide, YMnO\(_3\). When you consult the literature, it looks like there are many different approaches for making this material: solid-state synthesis, chimie douce methods, microwave-assisted synthesis, pulsed laser deposition, hydrothermal synthesis, etc.

In almost all of the papers you find, however, the authors describe significant difficulty in synthesizing phase-pure YMnO\(_3\). For example: - "... observation that crystallization at low temperature or high oxygen partial pressures gives a mixture of Y2Mn2O7 together with YMnO3" Brinks et al., Journal of Solid State Chemistry 129, 334-340 (1997). - "The solid state synthesis of YMnO3 requires very long procedure with repeated heating and grinding" Z. Brankovic et al. Ceramics International 41 (2015) - "There are still challenges to be addressed with respect to hydrothermal synthesis of h-YMnO3, most notably the difficulty in synthesising phase pure h-YMnO3. This is a result of the complexity of the system, with a total of eight crystalline phases having been detected throughout the course of the reaction." Marshall et al., Chem Eur. J 2020, 26, 9330-9337 (2020).

Being familiar with the Materials Project database and pymatgen, you decide to check the database to see if it can help answer the question: why is phase-pure YMnO\(_3\) so difficult to synthesize?

We previously learned how to use the MPRester to access computed data on the Materials Project. Let's start by importing MPRester:

1.1 EXERCISE: Acquiring entries from MP¶

Using the MPRester, acquire all entries from the Materials Project with the composition YMnO\(_3\) in the cell below:

1.2 Exploring downloaded entries¶

Now let's take a look at one of the downloaded entry objects.

In the ComputedStructureEntry printout, we can see the uncorrected energy, correction, final energy, and the various parameters/data associated with the calculation.

Since this is hard to interpret, it will be easier for us to reformat the entries into a pandas DataFrame with the relevant information. First we import pandas:

And then we create a function to help us wrangle the entries into the DataFrame format:

The dataframe can now be easily created by calling this function:

We see that there are several polymorphs of similar energy. The lowest energy polymorph is the hexagonal YMnO\(_3\) phase which is well known as the thermodynamically stable phase in the literature:

If we want to interactively view this structure in JupyterLab, we can also import crystal_toolkit to view it:

2. Building phase diagrams¶

Now that we've confirmed the existence of the target phase within the MP database, we'd like to better understand phase competition within the Y-Mn-O system. This means answering questions suchs as:

1. Just how stable is YMnO\(_3\)?
2. How much energy is released upon formation of YMnO\(_3\) from the corresponding binary oxides?
3. What other phases might compete against the formation of YMnO\(_3\)?
4. What kinds of oxygen chemical potentials stabilize YMnO\(_3\)?

These are all questions that can be answered by constructing phase diagrams within pymatgen.

2.1 EXERCISE: Acquiring all entries within the chemical system¶

Let's start by downloading entries for the full Y-Mn-O system using MPRester. How many entries exist within the full Y-Mn-O system?

2.2 Compositional phase diagrams¶

Now that we have all the entries within the Y-Mn-O system, we can create a ternary compositional phase diagram by simply passing the list of entries to create a PhaseDiagram object. Let's first import this class from the phase_diagram module:

And we can create the phase diagram:

To plot the phase diagram, we can either: 1. Create a PDPlotter object and call get_plot() with custom arguments 2. Create a PDPlotter object and call show() 3. In JupyterLab, just type the name of the phase diagram object in a cell and click "enter"!

Let's do option 1 so that we can see the possible arguments of the plotting function. First we import PDPlotter:

And then we create the plotting object and call the get_plot() function: